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The purpose of this paper is to improve the air movement operations planning heuristic in the literature to generate better solutions in a shorter time period.

Through a rigorous design of experiments (DOEs), we make significant heuristic improvements by evaluating alternative modular methodologies and tuning heuristic parameters for two scenarios. This includes a new approach to considering refueling operations.

We find the fine-tuned heuristic averages a 33% objective improvement and 70% reduction in computation time over the heuristic with original parameters for one of the scenarios. Additionally, we analyze the heuristic's quality of solution over time.

Further analysis is required to generalize heuristic settings, which would require significant access to operational data or a portfolio of scenarios of interest.

Tuned heuristic parameters reduce the computation time from hours to minutes. This also makes it practically feasible to adjust parameters in the objective function to generate multiple courses of action (COAs) for a given instance.

This research provides novel vehicle assignment and routing heuristic improvement alternatives and demonstrates a DOEs-based heuristic tuning procedure.

Despite the fact that chatbots have been largely adopted for the last few years, a comprehensive literature review research focusing on the intention of individuals to adopt chatbots is rather scarce. In this respect, the present paper attempts a literature review investigation of empirical studies focused on the specific issue in nine scientific databases during 2017-2021. Specifically, it aims to classify extant empirical studies which focus on the context of individuals' adoption intention toward chatbots.

The research is based on PRISMA methodology, which revealed a total of 39 empirical studies examining users' intention to adopt and utilize chatbots.

After a thorough investigation, distinct categorization criteria emerged, such as research field, applied theoretical models, research types, methods and statistical measures, factors affecting intention to adopt and further use chatbots, the countries/continents where these surveys took place as well as relevant research citations and year of publication. In addition, the paper highlights research gaps in the examined issue and proposes future research directions in such a promising information technology solution.

As far as the authors are concerned, there has not been any other comprehensive literature review research to focus on examining previous empirical studies of users' intentions to adopt and use chatbots on the aforementioned period. According to the authors' knowledge, the present paper is the first attempt in the field which demonstrates broad literature review data of relevant empirical studies.